Titlebook: Elements of Nonlinear Time Series Analysis and Forecasting; Jan G. De Gooijer Book 2017 Springer International Publishing Switzerland 2017

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Adrian W. T. Dostal,Gabriele Dostalan be achieved by using a nonlinear model instead of a familiar ARMA model. Therefore, one may wish to start the model building from a linear model and abandon it only if sufficiently strong evidence for a nonlinear alternative can be found. This approach can be applied using a linearity test, often

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Adrian W. T. Dostal,Tristan E. W. Dostalst a pre-chosen particular nonlinear alternative. Using the classical theory of statistical hypothesis testing, time-domain test nonlinearity tests can be based on three principles – the likelihood ratio (LR), Lagrange multiplier (LM), and Wald (W) principles. LRbased test statistics require estimat

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Chancen und Risiken der Kundenintegratione noise process is assumed to consist of i.i.d. random variables, and this hypothesis should be testable. Also, it is the first issue that gets raised when checking the adequacy of a fitted time series model through observed “residuals”, i.e. are they approximately i.i.d. or are there significant de

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Die Evolution des Innovationsmanagementsochastic process is said to be TR if its probabilistic structure is unaffected by reversing (“mirroring”) the direction of time. Otherwise, the process is said to be time-irreversible, or non-reversible. Confirmation of time-irreversibility is important because, according to Cox (1981), it is a symp

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Management von Intangible Assetsata up to a certain time t. In contrast, the situation becomes more complicated when real out-of-sample forecast are computed from parametric nonlinear time series models; in particular, as we explain below, this is a difficult issue for H ≥ 2 steps ahead.

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Unternehmensführung: Joint Ventures in Chinaehavior. Over the past few years, many multivariate (vector) nonlinear time series models have been proposed. Some of them are “ad - hoc”, with a special application in mind. Others are direct multivariate extensions of their univariate counterparts. Within the latter class, a definition of a multiv

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